torchfl
A Python library for rapid prototyping, experimenting, and logging of federated learning using state-of-the-art models and datasets. Built using PyTorch and PyTorch Lightning.
pfl
Simulation framework for accelerating research in Private Federated Learning
nerlnet
Nerlnet is a framework for research and development of distributed machine learning models on IoT
p3forecast
a Personalized Privacy Preserving cloud workload prediction framework based on Federated Generative Adversarial Networks (GANs), which allows cloud providers with Non-IID workload data to collaboratively train workload prediction models as preferred while protecting privacy.
https://github.com/aiot-mlsys-lab/fedaiot
[DMLR 2024] FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things
https://github.com/aiot-mlsys-lab/fedrolex
[NeurIPS 2022] "FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction" by Samiul Alam, Luyang Liu, Ming Yan, and Mi Zhang
https://github.com/aiot-mlsys-lab/pyramidfl
[MobiCom 2022] " PyramidFL: Fine-grained Data and System Heterogeneity-aware Client Selection for Efficient Federated Learning" by Chenning Li, Xiao Zeng, Mi Zhang, and Zhichao Cao.
federations_costs_slicing
This repository is the code basis of the paper intitled "The learning costs of Federated Learning in constrained scenarios"
feddistill
Code to reproduce the experiments of the ICLR25 paper "On the Byzantine-Resilience of Distillation-Based Federated Learning"
feddebug
FedDebug is a novel testing and debugging technique that localizes faulty clients in Federated Learning.
https://github.com/scimorph/secureml
Easy-to-use utilities to build privacy-preserving AI.
https://github.com/abtinmy/clustered-fl-brainage
Official implementation of paper "Brain Age Estimation Using Structural MRI: A Clustered Federated Learning Approach"
delicoco-ieee-transactions
In compressed decentralized optimization settings, there are benefits to having multiple gossip steps between subsequent gradient iterations, even when the cost of doing so is appropriately accounted for e.g. by means of reducing the precision of compressed information.
fedobp
FedOBP: Federated Optimal Brain Personalization with Few Personalized Parameters
adaptivebatchhe
An adaptive batch homomorphic encryption framework for cross-device Federated Learning, which determines cost-efficient and sufficiently secure encryption strategies for clients with heterogeneous data and system capabilities.
tno.fl.protocols.logistic-regression
TNO PET Lab - Federated Learning (FL) - Protocols - Logistic Regression
https://github.com/appfl/fedcompass
[ICLR 2024] FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler
fedless
Source code for the paper "FedLess: Secure and Scalable Federated Learning Using Serverless Computing" (IEEE BigData 2021)
fedfs
Federated Feature Selection as in the paper https://arxiv.org/abs/2109.11323
fl4health
A flexible, modular, and easy to use library to facilitate federated learning research and development in healthcare settings
awesome-federated-learning-for-autonomous-driving
FedML for Autonomous Driving (AD), Intelligent Transportation Systems (ITS), Connected and Automated Vehicles (CAV)
tno.fl.protocols.cox-regression
TNO PET Lab - Federated Learning (FL) - Protocols - Cox Regression
fed-rag
A framework for fine-tuning retrieval-augmented generation (RAG) systems.
awesome-federated-unlearning
Awesome Federated Unlearning (FU) Papers (Continually Update)
https://github.com/cpwan/attack-adaptive-aggregation-in-federated-learning
This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.
https://github.com/akassharjun/shapleyvaluefl
A pip library for calculating the Shapley Value for computing the marginal contribution of each client in a Federated Learning environment.